Children have been
increasingly becoming active users of the Internet and, although any segment of
the population is susceptible to falling victim to the existing risks, they in
particular are one of the most vulnerable. Thus, some of the major scourges of
this cybersociety are paedophile behaviours on the Internet, child pornography
or sexual exploitation of children. In light of this background, Negobot is a conversational agent posing as a
child, in chats, social networks and other channels suffering from paedophile
behaviour. As a conversational agent, Negobot, has a strong technical base of
Natural Language Processing and information retrieval, as well as Articial
Intelligence and Machine Learning. However, the most innovative proposal of
Negobot is to consider the conversation itself as a game, applying game theory.

In this context,
Negobot proposes, first, a competitive game in which the system identies the
best strategies for achieving its goal, to obtain information that leads us to
infer if the subject involved in a conversation with the agent has paedophile
tendencies, while our actions do not bring the alleged offender to leave the
conversation due to a suspicious behaviour of the agent.